1. Field of the Invention
The field of the present invention relates to systems and methods for monitoring and assessing the performance and operation of fabrication facilities, such as semiconductor fabrication facilities.
2. Brief Description of Related Developments
The manufacture of microelectronic circuits and/or components on semiconductor wafers can be a complex and involved process, requiring numerous tools and machines operating in a production sequence according to a specified set of instructions (e.g., a xe2x80x9crecipexe2x80x9d). Examples of fabrication processes typically performed in the manufacture of a semiconductor wafer include etching, deposition, diffusion, and cleaning.
Large semiconductor fabrication facilities can have dozens or even hundreds of tools, each of which is called upon periodically to perform part of a process as dictated by the selected recipe(s). Some fabrication tools are used for processing semiconductor wafers, while others, known as metrology tools, are generally used for measuring the output of a processing tool. Fabrication tools are often employed in an assembly-line fashion, with each applicable tool having a role in the step-by-step fabrication of a semiconductor wafer. However, due to the nature of the step-by-step manufacturing processes, at least some tools will be idle at any given time, waiting for the output of an upstream tool. Fabrication tools can also be idle for other reasons, such as when needing maintenance, repair or re-programming, or re-configuration with respect to other tools in the plant. The amount of time fabrication tools are idle bears a correlation, directly or indirectly, to the overall efficiency of a semiconductor fabrication facility, and hence a correlation to the profitability of the facility. A challenge for each fabrication facility is thus to reduce idle time of fabrication tools to the maximum extent possible, therefore maximizing production time, yield and profitability.
Moreover, many processing tools and metrology tools are quite expensive, and the collective array of tools brought together at a semiconductor fabrication facility represent a substantial investment. To the extent tools are idle, the investment in these tools is wasted. The floor space at semiconductor fabrication facilities is also enormously expensive, due to extreme requirements of cleanliness, among other reasons, and so even inexpensive tools which are idle can be costly in terms of wasted floor space that is being underutilized. Furthermore, large semiconductor fabrication facilities often will have many duplicate tools for performing processes in parallel. If facility engineers can determine that certain duplicate tools are idle for long periods, then some of the duplicate tools can potentially be eliminated, saving both the cost of the tools and the floor space that they take up. Alternatively, if all of a certain type of tool is operating at maximum efficiency yet still are the cause of a bottleneck in the manufacturing process, production engineers may determine that more tools need to be purchased. Therefore, a tremendous need exists to identify which fabrication tools are active and which idle, and for what reasons. For example, if a fabrication tool was idle for a long period because the upstream process step takes a long time, a production engineer may come to a different conclusion about how to adjust facility resources than if the idle period was due to the fact that the upstream fabrication tool was broken and needed to be repaired. Thus, the reason for tool idleness can be important information for engineers controlling semiconductor manufacturing processes.
To assist production engineers in assessing semiconductor manufacturing efficiency, a variety of informational reporting standards have been promulgated. One of the earliest such standards is known as the E10-0699 Standard for Definition and Measurement of Equipment Reliability, Availability and Maintainability (RAM) (hereinafter the xe2x80x9cE10 Standardxe2x80x9d), hereby incorporated by reference as if set forth fully herein. This standard, originally put forward around 1986 by Semiconductor Equipment and Materials International (SEMI), defines six basic equipment states into which all equipment conditions and periods of time (either productive or idle time) must fall. Total time for each tool is divided into Operations Time and Non-Scheduled Time. Operations Time is divided into five different categories (Unscheduled Downtime, Scheduled Downtime, Engineering Time, Standby Time, and Productive Time) which, together with Non-Scheduled Time, comprise the six basic equipment states. Equipment Downtime for a given tool is divided into Unscheduled Downtime and Schedule Downtime. Likewise, Equipment Uptime for a given tool is divided into Engineering Time, Standby Time and Productive Time. Of these three Equipment Uptime states, Productive Time and Standby Time collectively represent the Manufacturing Time for a given tool.
The E10 Standard also defines a number of reliability, availability and maintainability measurements relating to equipment performance. Such measurements include, for example, mean (productive) time between interrupts (MTBI), mean (productive) time between failures (MTBF), mean (productive) time between assists (MTBA), mean cycles between interrupts (MCBI), mean cycles between failures (MCBF), and mean cycles between assists (MCBA). Mean (productive) time between interrupts (MTBI) indicates the average time that the tool or equipment performed its intended function between interrupts, and is calculated as the productive time divided by the number of interrupts during that time. Mean (productive) time between failures (MTBF) indicates the average time the tool or equipment performed its intended function between failures, and is calculated as the productive time divided by the number of failures during that time. Mean (productive) time between assists (MTBA) indicates the average time the tool or equipment performed its intended function between assists, and is calculated as the productive time divided by the number of assists during that time. Mean cycles between interrupts (MCBI), mean cycles between failures (MCBF), and mean cycles between assists (MCBA) are similar, but relate the number of tool or equipment cycles to the number of interrupts, failures and assists, rather than the productive time. The E10 Standard also provides guidelines for calculating equipment dependent uptime, supplier dependent uptime, operational uptime, mean time to repair (average time to correct a failure or an interrupt), mean time off-line (average time to maintain the tool or equipment or return it to a condition in which it can perform its intended function), equipment dependent scheduled downtime, supplier dependent scheduled downtime, operational utilization, and total utilization. The E10 Standard provides for calculation of two important metrics in particular: Overall Equipment Effectiveness (OEE), and Overall Fabrication Effectiveness (OFE). Traditionally, most of the information used to calculate the metrics in the E10 Standard has been gathered manuallyxe2x80x94a slow, tedious process prone to potential errors.
Since its inception, the E10 Standard has been refined and improved upon. In recent years, at least two new standards have been proposed or adopted by SEMI, the same entity that originally proposed the E10 Standard. The first of these new standards is known as the E58-0697 Automated Reliability, Availability and Maintainability Standard (ARAMS) (hereinafter the xe2x80x9cE58 Standardxe2x80x9d), and the second is known as the E79 Standard for Definition and Measurement of Equipment Productivity (hereinafter the xe2x80x9cE79 Standardxe2x80x9d). The E58 Standard was proposed around 1997 in an attempt to integrate automated machine processes into the E10 Standard. Accordingly, the E58 Standard specifies triggers for state transitions described in the E10 Standard, with the intent of encouraging tool or equipment manufacturers to store and make available trigger information at each tool. As the E58 Standard was apparently envisioned, tool and equipment manufacturers would include special software with their tools and equipment, allowing controllers or monitoring equipment to read information about trigger events that could be gathered and used in the calculations of tool availability, reliability and maintainability. However, very few tool and equipment manufacturers have actually written such special software for their tools and equipment. One possible reason for the reluctance to include such software is that, if productivity information were available to their customers, tool and equipment manufacturers might be required to extend warranty periods for their tools and equipment for periods of time in which the equipment was not up and running. Therefore, tool and equipment manufacturers have an incentive not to provide software that meets the guidelines of the E58 Standard.
More recently, the E79 standard has been proposed. The E79 Standard builds upon the E10 and E58 Standards, and specifies, among other things, a set of metrics for calculating certain reporting items. Two such metrics are referred to as the Overall Equipment Efficiency (OEE) metric and Overall Fabrication Efficiency (OFE) metric. The E79 Standard also specifies metrics for determining, for example, Availability Efficiency, Performance Efficiency, Operational Efficiency, Rate Efficiency, Theoretical Production Time, and Quality Efficiency, among others.
While the E10, E58 and E79 Standards all provide guidelines for assessing equipment availability, reliability and maintainability, they do not describe how to gather and process the necessary information. These tasks can be quite challenging. For example, different platforms are used in different semiconductor fabrication facilities for communicating between supervisory equipment and various processing and measurement tools. Therefore, a single information gathering technique might not be possible for all fabrication facilities. Furthermore, despite the existence of the E58 Standard, few tools actually store the trigger and event information that facilitates the calculation of various performance and efficiency metrics covered by the standards. Thus, obtaining the necessary data can be difficult. In addition, multi-chamber tools (also known as cluster tools) pose a problem, because they involve equipment with multiple subsidiary tools treated as a single unit. The standards indicate a preference that information concerning the individual subsidiary tools be available, as opposed to merely information about the cluster tool as a whole.
While having an automated way of gathering and processing information useful for monitoring and assessing tool and equipment performance according to the various available standards would be highly beneficial, actual implementations of systems for performing these activities may be undesirable if they require modifications to existing control systems which are deployed in semiconductor fabrication facilities. Owners of such facilities may be very reluctant to make changes that would impact their existing control systems, because of the potential for introducing xe2x80x9cbugsxe2x80x9d or errors into the system, or causing other unforeseen consequences. Moreover, actual implementations of systems for monitoring or assessing tool and equipment performance according to the various standards may also be undesirable if they require modifications to the existing processing or metrology tools. Tool manufacturers may be quite reluctant to make changes that might impact the performance of their tools, such as changing the message driver of the tools, or that might lead to incompatibilities with existing versions of tools, interface equipment, or control systems. Moreover, tool manufacturers may simply want to avoid the expense of re-designing their tools to provide the functionality that may be required for monitoring or assessing tool and equipment performance.
It would therefore be advantageous to provide a non-intrusive, reliable and comprehensive system or method for monitoring, assessing and reporting the operation and performance of semiconductor or other types of fabrication facilities. It would further be advantageous to provide such a system or method that requires a minimum of modifications to existing control systems, tools or equipment.
In accordance with a first embodiment of the invention, a method for monitoring and assessing operation of a semiconductor fabrication facility comprises the steps of connecting a monitoring and assessment system to a system bus which is connected directly or indirectly to a manufacturing execution system and a plurality of semiconductor fabrication tools. Through a user interface, the state models for each fabrication tool can be configured where each state model is based upon a set of defined triggers for each tool. During monitoring various messages are transmitted on the system bus between the semiconductor fabrication tools and the manufacturing execution system and the monitoring and assessment system, and appropriate triggers are generated based upon the messages where the triggers are selected from a set of defined triggers. During operation, the state models are updated for each tool affected by one of the triggers and transitions within the state models are recorded in a tracking database.
In another embodiment of the invention, a system for monitoring and assessing operation of a semiconductor fabrication facility for assessing overall equipment effectiveness and overall fabrication effectiveness comprises a monitoring and assessment system for receiving messages having equipment information therein for tracking operation states of a plurality of semiconductor fabrication tools. A manufacturing execution system for controlling the manufacture of semiconductor wafers or other products according to a programmed recipe sends commands to the semiconductor fabrication tools, monitors their activity and sends messages to the monitoring and assessment system. These messages are transmitted over a system bus that is connected directly or indirectly to the manufacturing execution system and the monitoring and assessment system. A user interface can monitor the messages transmitted on the system bus between the semiconductor fabrication tools and the manufacturing execution system and the monitoring and assessment system. A user may configure state models for the semiconductor fabrication tools in which the state models are based upon a set of defined triggers for each tool. Base on the trigger information and other events, the state transitions are maintained in a tracking database for recording state transitions within the state models.
As a further embodiment of the present invention, a monitoring and assessment system for monitoring and assessing operation of a semiconductor fabrication facility assesses overall equipment and overall fabrication effectiveness. The monitoring and assessment system comprises a trigger/event interface for receiving messages having fabrication tool information therein for tracking operation states of a plurality of semiconductor fabrication tools. A state model logic receives the tracking operation information for each fabrication tool having defined states and a state transition logic defining triggering events and the state transitions related to the triggering event. If the fabrication tool has a state change, a state change transition logger inputs this information into a tracking database for recording transition information. A report generator with metric calculation logic therein may generate performance metrics for the fabrication tools which is used for assessing overall equipment effectiveness and overall fabrication effectiveness of the fabrication tools. A user interface may monitor and configure state models for the semiconductor fabrication tools in the state model logic, may configure trigger/event information in the trigger/event interface, may monitor state transitions in the tracking database, and may monitor equipment effectiveness and overall fabrication effectiveness of the fabrication tools.